---
base_model: microsoft/phi-4
library_name: peft
license: mit
datasets:
- vicgalle/alpaca-gpt4
language:
- en
pipeline_tag: text-generation
---

# Model Card for FlowerTune-phi-4-NLP-PEFT

This PEFT adapter has been trained by using [Flower](https://flower.ai/), a friendly federated AI framework.

The adapter and benchmark results have been submitted to the [FlowerTune LLM NLP Leaderboard](https://flower.ai/benchmarks/llm-leaderboard/nlp/).

## Model Details

Please check the following GitHub project for model details and evaluation results:

[https://github.com/mrs83/FlowerTune-phi-4-NLP](https://github.com/mrs83/FlowerTune-phi-4-NLP)

## How to Get Started with the Model

Use this model as:

```
from peft import PeftModel
from transformers import AutoModelForCausalLM

base_model = AutoModelForCausalLM.from_pretrained("microsoft/phi-4")
model = PeftModel.from_pretrained(base_model, "mrs83/FlowerTune-phi-4-NLP-PEFT")
```

### Evaluation Results (Accuracy)

- **STEM**: 40.66 %
- **Social Sciences**: 74.52 %
- **Humanities**: 51.75 %
- **Average**: 55.64 %

### Communication Budget

45804.69  Megabytes

### Framework versions

- PEFT 0.14.0
- Flower 1.13.0